Customer Analytics Gone Wrong – Eight Common Mistakes to Avoid When Deploying Customer Analytics Models


Book Description

Designing customer analytics models is only half the battle. Equally, if not more difficult, is deploying them, such that actions triggered by the model outputs are being taken on a daily basis. In this follow-up article, we highlight some of the most commonly made mistakes that prevent companies from succeeding at deploying models…




Customer Analytics Gone Wrong – Ten Common Mistakes To Avoid When Designing Customer Analytics Models


Book Description

The potential that customer analytics models hold within them are extensive for the companies that choose to utilize them to better their marketing and sales activities. But even best-in-class companies get it wrong sometimes by making mistakes in how they design their models, and in how they utilize them once they have been designed. Herein we present ten mistakes to avoid in designing customer analytics models…




Predictive Marketing


Book Description

Make personalized marketing a reality with this practical guide to predictive analytics Predictive Marketing is a predictive analytics primer for organizations large and small, offering practical tips and actionable strategies for implementing more personalized marketing immediately. The marketing paradigm is changing, and this book provides a blueprint for navigating the transition from creative- to data-driven marketing, from one-size-fits-all to one-on-one, and from marketing campaigns to real-time customer experiences. You'll learn how to use machine-learning technologies to improve customer acquisition and customer growth, and how to identify and re-engage at-risk or lapsed customers by implementing an easy, automated approach to predictive analytics. Much more than just theory and testament to the power of personalized marketing, this book focuses on action, helping you understand and actually begin using this revolutionary approach to the customer experience. Predictive analytics can finally make personalized marketing a reality. For the first time, predictive marketing is accessible to all marketers, not just those at large corporations — in fact, many smaller organizations are leapfrogging their larger counterparts with innovative programs. This book shows you how to bring predictive analytics to your organization, with actionable guidance that get you started today. Implement predictive marketing at any size organization Deliver a more personalized marketing experience Automate predictive analytics with machine learning technology Base marketing decisions on concrete data rather than unproven ideas Marketers have long been talking about delivering personalized experiences across channels. All marketers want to deliver happiness, but most still employ a one-size-fits-all approach. Predictive Marketing provides the information and insight you need to lift your organization out of the campaign rut and into the rarefied atmosphere of a truly personalized customer experience.




Business Intelligence


Book Description

Business professionals who want to advance their careers need to have a strong understanding of how to utilize business intelligence. This new book provides a comprehensive introduction to the basic business and technical concepts they’ll need to know. It integrates case studies that demonstrate how to apply the material. Business professionals will also find suggested further readings that will develop their knowledge and help them succeed.




Fundamentals of Machine Learning for Predictive Data Analytics, second edition


Book Description

The second edition of a comprehensive introduction to machine learning approaches used in predictive data analytics, covering both theory and practice. Machine learning is often used to build predictive models by extracting patterns from large datasets. These models are used in predictive data analytics applications including price prediction, risk assessment, predicting customer behavior, and document classification. This introductory textbook offers a detailed and focused treatment of the most important machine learning approaches used in predictive data analytics, covering both theoretical concepts and practical applications. Technical and mathematical material is augmented with explanatory worked examples, and case studies illustrate the application of these models in the broader business context. This second edition covers recent developments in machine learning, especially in a new chapter on deep learning, and two new chapters that go beyond predictive analytics to cover unsupervised learning and reinforcement learning.




Advanced Information Systems Engineering


Book Description

This book constitutes the refereed proceedings of the 32nd International Conference on Advanced Information Systems Engineering, CAiSE 2020, held in Grenoble, France, in June 2020.* The 33 full papers presented in this volume were carefully reviewed and selected from 185 submissions. The book also contains one invited talk in full paper length. The papers were organized in topical sections named: distributed applications; AI and big data in IS; process mining and analysis; requirements and modeling; and information systems engineering. Abstracts on the CAiSE 2020 tutorials can be found in the back matter of the volume. *The conference was held virtually due to the COVID-19 pandemic.




Business Modeling


Book Description

As business modeling becomes mainstream, every year more and more companies and government agencies are creating models of their businesses. But creating good business models is not a simple endeavor. Business modeling requires new skills. Written by two business modeling experts, this book shows you how to make your business modeling efforts successful. It provides in-depth coverage of each of the four distinct business modeling disciplines, helping you master them all and understand how to effectively combine them. It also details best practices for working with subject matter experts. And it shows how to develop models, and then analyze, simulate, and deploy them. This is essential, authoritative information that will put you miles ahead of everyone who continues to approach business modeling haphazardly. - Provides in-depth coverage of the four business modeling disciplines: process modeling, motivation modeling, organization modeling, and rules modeling - Offers guidance on how to work effectively with subject matter experts and how to run business modeling workshops - Details today's best practices for building effective business models, and describes common mistakes that should be avoided - Describes standards for each business modeling discipline - Explains how to analyze, simulate, and deploy business models - Includes examples both from the authors' work with clients and from a single running example that spans the book




HBR Insights Future of Business Boxed Set (8 Books)


Book Description

Business is changing. Will you adapt or be left behind? Get up to speed and deepen your understanding of the topics that are shaping your company's future with the Insights You Need from Harvard Business Review series. Featuring HBR's smartest thinking on fast-moving issues, each book provides the foundational introduction and practical case studies your organization needs to compete today and collects the best research, interviews, and analysis to get it ready for tomorrow. You can't afford to ignore how these issues will transform the landscape of business and society. The Insights You Need series will help you grasp these critical ideas—and prepare you and your company for the future. This specially priced 8-volume set includes: Agile Artificial Intelligence Blockchain Climate Change Customer Data & Privacy Cybersecurity Monopolies & Tech Giants Strategic Analytics




Powering the Digital Economy: Opportunities and Risks of Artificial Intelligence in Finance


Book Description

This paper discusses the impact of the rapid adoption of artificial intelligence (AI) and machine learning (ML) in the financial sector. It highlights the benefits these technologies bring in terms of financial deepening and efficiency, while raising concerns about its potential in widening the digital divide between advanced and developing economies. The paper advances the discussion on the impact of this technology by distilling and categorizing the unique risks that it could pose to the integrity and stability of the financial system, policy challenges, and potential regulatory approaches. The evolving nature of this technology and its application in finance means that the full extent of its strengths and weaknesses is yet to be fully understood. Given the risk of unexpected pitfalls, countries will need to strengthen prudential oversight.




Advanced Analytics Methodologies


Book Description

Advanced Analytics Methodologies is today's definitive guide to analytics implementation for MBA and university-level business students and sophisticated practitioners. Its expanded, cutting-edge coverage helps readers systematically "jump the gap" between their organization's current analytical capabilities and where they need to be. Step by step, Michele Chambers and Thomas Dinsmore help readers customize a complete roadmap for implementing analytics that supports unique corporate strategies, aligns with specific corporate cultures, and serves unique customer and stakeholder communities. Drawing on work with dozens of leading enterprises, Michele Chambers and Thomas Dinsmore provide advanced applications and examples not available elsewhere, describe high-value applications from many industries, and help you systematically identify and deliver on your company's best opportunities. They show how to: Go beyond the Analytics Maturity Model: power your unique business strategy with an equally focused analytics strategy Link key business objectives with core characteristics of your organization, value chain, and stakeholders Take advantage of game changing opportunities before competitors do Effectively integrate the managerial and operational aspects of analytics Measure performance with dashboards, scorecards, visualization, simulation, and more Prioritize and score prospective analytics projects Identify "Quick Wins" you can implement while you're planning for the long-term Build an effective Analytic Program Office to make your roadmap persistent Update and revise your roadmap for new needs and technologies This advanced text will serve the needs of students and faculty studying cutting-edge analytics techniques, as well as experienced analytics leaders and professionals including Chief Analytics Officers; Chief Data Officers; Chief Scientists; Chief Marketing Officers; Chief Risk Officers; Chief Strategy Officers; VPs of Analytics or Big Data; data scientists; business strategists; and many line-of-business executives.